Variation in correlation between prognosis and histologic feature based on biopsy selection

03/04/2020
by   Emily Diller, et al.
0

Glioblastoma multiform carries a dismal prognosis with poor response to gold standard treatment. Innovative data analysis methods have been developed to characterize tumor genomic expression with histologic features. In a clinical setting, biopsy selection methods may be constrained by time and financial burden to the patient. Thus, we investigate the impact biopsy selection has on correlation between prognostic and histologic features in 35 patients with GBM. We compared methods using limited volumes, moderate volumes, and enblock tumor volumes. Additionally, we investigated the impact of random versus strategic methods for limited and moderate volume biopsies. Finally, we compared correlation results by selecting one to five small biopsy. We observed a wide range in correlation significance across selection methods. These findings may aid clinical management of GBM and direct better biopsy selection necessary for the development and deployment of targeted therapies.

READ FULL TEXT
research
04/29/2022

Preoperative brain tumor imaging: models and software for segmentation and standardized reporting

For patients suffering from brain tumor, prognosis estimation and treatm...
research
06/05/2023

Brain Tumor Recurrence vs. Radiation Necrosis Classification and Patient Survivability Prediction

GBM (Glioblastoma multiforme) is the most aggressive type of brain tumor...
research
08/16/2023

Prediction of post-radiotherapy recurrence volumes in head and neck squamous cell carcinoma using 3D U-Net segmentation

Locoregional recurrences (LRR) are still a frequent site of treatment fa...
research
10/13/2018

Social Media Brand Engagement as a Proxy for E-commerce Activities: A Case Study of Sina Weibo and JD

E-commerce platforms facilitate sales of products while product vendors ...

Please sign up or login with your details

Forgot password? Click here to reset